Evaluating the role of human papillomavirus vaccine in cervical cancer prevention

Analysis of longitudinal multivariate outcome data from couples cohort studies: application to HPV transmission dynamics

We consider a specific situation of correlated data where multiple outcomes are repeatedly measured on each member of a couple. Such multivariate longitudinal data from couples may exhibit multi-faceted correlations which can be further complicated if there are polygamous partnerships. An example is data from cohort studies on human papillomavirus (HPV) transmission dynamics in heterosexual couples. HPV is a common sexually transmitted disease with 14 known oncogenic types causing anogenital cancers. The binary outcomes on the multiple types measured in couples over time may introduce inter-type, intra-couple, and temporal correlations. Simple analysis using generalized estimating equations or random effects models lacks interpretability and cannot fully utilize the available information. We developed a hybrid modeling strategy using Markov transition models together with pairwise composite likelihood for analyzing such data. The method can be used to identify risk factors associated with HPV transmission and persistence, estimate difference in risks between male-to-female and female-to-male HPV transmission, compare type-specific transmission risks within couples, and characterize the inter-type and intra-couple associations. Applying the method to HPV couple data collected in a Ugandan male circumcision (MC) trial, we assessed the effect of MC and the role of gender on risks of HPV transmission and persistence.

Evaluation of operational chronic infection endpoints for HCV vaccine trials

Hepatitis C virus (HCV) is a leading cause of chronic liver disease. The natural history of HCV infection is heterogeneous, and a person infected with HCV can clear the virus or progress to a chronic infection. The chronic infection can remain asymptomatic for decades before the development of liver cirrhosis and/or carcinoma. Currently, there are no assays that can differentiate a transient infection (an acute infection that would clear) from a chronic infection, and serial HCV RNA testing is used to operationally define chronic hepatitis C (e.g. detectable HCV over 6 months). Therefore, HCV vaccine trial planning can benefit from the assessment of the endpoint candidates that are aimed at the chronic infection. Operationally defined endpoints based on the virological tests at study visits have been previously studied in the context of human papillomavirus (HPV) vaccine trials. However, HCV natural history is different from HPV, requiring separate considerations. In this work, several definitions of chronic infection that are based on the periodically observed HCV RNA statuses are evaluated, using a multi-state, time-homogeneous Markov model for transient and chronic infections under various infection settings. Our results show some inflation in the type I error in the log-rank test on the vaccine efficacy against chronic infections in the presence of vaccine efficacy related to transient infections. A type I error up to almost four times the planned rate of 5% is observed in one setting. Overall, simple operational endpoints yield higher power than more complex endpoints, but the simplest endpoint is most affected by the type I error inflation and misclassification error due to the assay imperfection.

Prevalence of human papillomavirus cervical infection in an Italian asymptomatic population

Background

In the last decade many studies have definitely shown that human papillomaviruses (HPVs) are the major cause of cervical carcinogenesis and, in the last few years, HPV testing has been proposed as a new and more powerful tool for cervical cancer screening. This issue is now receiving considerable attention in scientific and non scientific press and HPV testing could be considered the most important change in this field since the introduction of cervical cytology. This paper reports our prevalence data of HPV infection collected in the '90s, while a follow up of these patients is ongoing.

Methods

For this study we used polymerase chain reaction (PCR) to search HPV DNA sequences in cervical cell scrapings obtained from 503 asymptomatic women attending regular cervical cancer screening program in the city of Genova, Italy. All patients were also submitted to a self-administered, standardized, questionnaire regarding their life style and sexual activity. On the basis of the presence of HPV DNA sequences women were separated into two groups: "infected" and "non infected" and a statistical analysis of the factors potentially associated with the infection group membership was carried out.

Results

The infection rate was 15.9% and the most frequent viral type was HPV 16.

Conclusion

Our HPV positivity rate (15.9%) was consistent to that reported by other studies on European populations.

Evaluation of log-rank tests for infrequent observations from a multi-state process, with application to HPV vaccine efficacy

Genital infection by human papillomavirus (HPV) is a common sexually transmitted disease, with over 25 per cent prevalence among young women in the US. Infections are usually without symptoms and transient (or reversible), but a small proportion of infections persist and are believed to be responsible for nearly all cervical cancers and precursor lesions such as cervical intraepithelial neoplasia (CIN). Therefore, successful vaccines against persistent HPV infections could have a great impact in preventing cervical cancers. In trials being planned, ongoing, and recently completed, a log-rank or a similar test may be employed to assess a vaccine effect in comparison to placebo, with an infection 'event' defined to capture persistent but not transient infections. However, it is not clear how best to define such an event, because (1) diagnostic tests cannot distinguish a persistent from a transient infection, (2) participants are only examined periodically, and (3) there can be misclassification errors in the detection of infections. This paper evaluates several definitions of persistent infection that are based on periodically observed infection statuses by postulating a multi-state model for persistent and transient infections. The type I error and the power of tests on vaccine efficacy based on these operational definitions are then examined under various scenarios of how a vaccine might affect the infection-disease process. We find that none of the candidates performs satisfactorily, thus raising concerns that clinical trials based only on infection endpoints will not be reliable.